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Characterization of general ridge estimators

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  • Markiewicz, Augustyn

Abstract

The general ridge estimators are characterized as linearly sufficient and admissible among the set of all linear estimators under a nonsingular linear model. Their counterparts, in some more general models, are presented.

Suggested Citation

  • Markiewicz, Augustyn, 1996. "Characterization of general ridge estimators," Statistics & Probability Letters, Elsevier, vol. 27(2), pages 145-148, April.
    • Handle: RePEc:eee:stapro:v:27:y:1996:i:2:p:145-148
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    References listed on IDEAS

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    1. Mueller, Jochen, 1987. "Sufficiency and completeness in the linear model," Journal of Multivariate Analysis, Elsevier, vol. 21(2), pages 312-323, April.
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    Cited by:

    1. Heiligers, Berthold & Markiewicz, Augustyn, 1996. "Linear sufficiency and admissibility in restricted linear models," Statistics & Probability Letters, Elsevier, vol. 30(2), pages 105-111, October.
    2. Ibarrola, P. & Pérez-Palomares, A., 2004. "Linear completeness in a continuous time Gauss-Markov model," Statistics & Probability Letters, Elsevier, vol. 69(2), pages 143-149, August.
    3. Koji Tsukuda & Hiroshi Kurata, 2020. "Covariance structure associated with an equality between two general ridge estimators," Statistical Papers, Springer, vol. 61(3), pages 1069-1084, June.
    4. Buatikan Mirezi & Selahattin Kaçıranlar, 2023. "Admissible linear estimators in the general Gauss–Markov model under generalized extended balanced loss function," Statistical Papers, Springer, vol. 64(1), pages 73-92, February.
    5. Markiewicz, Augustyn, 1998. "Comparison of linear restricted models with respect to the validity of admissible and linearly sufficient estimators," Statistics & Probability Letters, Elsevier, vol. 38(4), pages 347-354, July.
    6. Ibarrola, P. & Pérez-Palomares, A., 2003. "Linear sufficiency and linear admissibility in a continuous time Gauss-Markov model," Journal of Multivariate Analysis, Elsevier, vol. 87(2), pages 315-327, November.

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